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检索条件"任意字段=Multisensor. Multisource Information Fusion: Architectures, Algorithms, and Applications 2003"

共 284 条记录，以下是91-100 订阅

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fusion of Hyperspectral and LADAR Data for Autonomous Target Detection

Fusion of Hyperspectral and LADAR Data for Autonomous Target...

引用

Conference on multisensor. multisource information fusion - architectures, algorithms, and applications

作者： Kanaev, A. V. Walls, T. J. USN Res Lab Washington DC 20375 USA

ISBN: (纸本)9780819486387

Robust fusion of data from disparate sensor modalities can provide improved target detection performance over those attainable with the individual sensors. In particular, detection of low-radiance manmade objects or objects under shadow obscuration in hyperspectral imagery (HSI) with acceptable false alarm rates has proven especially challenging. We have developed a fusion algorithm for the enhanced detection of difficult targets when the HSI data is simultaneously collected with LADAR data. Initial detections are obtained by applying a sub-space RX (SSRX) algorithm to the HSI data. In parallel, LADAR-derived digital elevation map (DEM) is segmented and coordinates of objects within a specific elevation range and size are returned to the HSI processor for their spectral signature extraction. Each extracted signature that has not been already detected by SSRX is used in secondary HSI detection employing the adaptive cosine estimator (ACE) algorithm. We show that spatial distribution of ACE score allows for confident discrimination between background elevations and manmade objects. Key to cross-characterization of the data is the accurate co-alignment of the image data. We have also developed an algorithm for automatic co-registration of ladar and HSI imagery, based on the maximization of mutual information, which can provide accurate, sub-pixel registration even if the case when the imaging geometries for the two sensors differ. Details of both algorithms will be presented and results from application to field data will be discussed.

关键词： data fusion hyperspectral imagery LADAR registration maximization of mutual information

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ULTRASONIC IMAGING OF MATERIAL FLAWS EXPLOITING MULTIPATH information

ULTRASONIC IMAGING OF MATERIAL FLAWS EXPLOITING MULTIPATH IN...

引用

Conference on multisensor. multisource information fusion - architectures, algorithms, and applications

作者： Shen, Xizhong Zhang, Yimin D. Demirli, Ramazan Amin, Moeness G. Villanova Univ Ctr Adv Commun Villanova PA 19085 USA Shanghai Inst Technol Elect & Automat Sch Shanghai Peoples R China

ISBN: (纸本)9780819486387

In this paper, we consider ultrasonic imaging for the visualization of flaws in a material. Ultrasonic imaging is a powerful nondestructive testing (NDT) tool which assesses material conditions via the detection, localization, and classification of flaws inside a structure. Multipath exploitations provide extended virtual array apertures and, in turn, enhance imaging capability beyond the limitation of traditional multisensor.approaches. We utilize reflections of ultrasonic signals which occur when encountering different media and interior discontinuities. The waveforms observed at the physical as well as virtual sensors yield additional measurements corresponding to different aspect angles. Exploitation of multipath information addresses unique issues observed in ultrasonic imaging. (1) Utilization of physical and virtual sensors significantly extends the array aperture for image enhancement. (2) Multipath signals extend the angle of view of the narrow beamwidth of the ultrasound transducers, allowing improved visibility and array design flexibility. (3) Ultrasonic signals experience difficulty in penetrating a flaw, thus the aspect angle of the observation is limited unless access to other sides is available. The significant extension of the aperture makes it possible to yield flaw observation from multiple aspect angles. We show that data fusion of physical and virtual sensor data significantly improves the detection and localization performance. The effectiveness of the proposed multipath exploitation approach is demonstrated through experimental studies.

关键词： Ultrasonic imaging information fusion multipath exploitation nondestructive evaluation flaw detection

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Implementation and testing of a sensor-netting algorithm for early warning and high confidence C/B threat detection

Implementation and testing of a sensor-netting algorithm for...

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Conference on multisensor. multisource information fusion - architectures, algorithms, and applications

作者： Gruber, Thomas Grim, Larry Fauth, Ryan Tercha, Brian Powell, Chris Steinhardt, Kristin MESH Inc Oxford PA 19363 USA

ISBN: (纸本)9780819486387

Large networks of disparate chemical/biological (C/B) sensors, MET sensors, and intelligence, surveillance, and reconnaissance (ISR) sensors reporting to various command/display locations can lead to conflicting threat information, questions of alarm confidence, and a confused situational awareness. Sensor netting algorithms (SNA) are being developed to resolve these conflicts and to report high confidence consensus threat map data products on a common operating picture (COP) display. A data fusion algorithm design was completed in a Phase I SBIR effort and development continues in the Phase II SBIR effort. The initial implementation and testing of the algorithm has produced some performance results. The algorithm accepts point and/or standoff sensor data, and event detection data (e. g., the location of an explosion) from various ISR sensors (e.g., acoustic, infrared cameras, etc.). These input data are preprocessed to assign estimated uncertainty to each incoming piece of data. The data are then sent to a weighted tomography process to obtain a consensus threat map, including estimated threat concentration level uncertainty. The threat map is then tested for consistency and the overall confidence for the map result is estimated. The map and confidence results are displayed on a COP. The benefits of a modular implementation of the algorithm and comparisons of fused /un-fused data results will be presented. The metrics for judging the sensor-netting algorithm performance are warning time, threat map accuracy (as compared to ground truth), false alarm rate, and false alarm rate v. reported threat confidence level.

关键词： sensor netting algorithm fusion tomography map uncertainty consistency

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fusion of Chemical, Biological, and Meteorological Observations for Agent Source Term Estimation and Hazard Refinement

Fusion of Chemical, Biological, and Meteorological Observati...

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Conference on multisensor. multisource information fusion - architectures, algorithms, and applications

作者： Bieringer, Paul E. Rodriguez, Luna M. Sykes, Ian Hurst, Jonathan Vandenberghe, Francois Weil, Jeffrey Bieberbach, George Parker, Steve Cabell, Ryan Natl Ctr Atmospher Res POB 3000 Boulder CO 80307 USA Sage Management Princeton NJ 08540 USA

ISBN: (纸本)9780819486387

Chemical and biological (CB) agent detection and effective use of these observations in hazard assessment models are key elements of our nation's CB defense program that seeks to ensure that Department of Defense (DoD) operations are minimally affected by a CB attack. Accurate hazard assessments rely heavily on the source term parameters necessary to characterize the release in the transport and dispersion (T&D) simulation. Unfortunately, these source parameters are often not known and based on rudimentary assumptions. In this presentation we describe an algorithm that utilizes variational data assimilation techniques to fuse CB and meteorological observations to characterize agent release source parameters and provide a refined hazard assessment. The underlying algorithm consists of a combination of modeling systems, including the Second order Closure Integrated PUFF model (SCIPUFF), its corresponding Source Term Estimation (STE) model, a hybrid Lagrangian-Eulerian Plume Model (LEPM), its formal adjoint, and the software infrastructure necessary to link them. SCIPUFF and its STE model are used to calculate a "first guess" source estimate. The LEPM and corresponding adjoint are then used to iteratively refine this release source estimate using variational data assimilation techniques. This algorithm has undergone preliminary testing using virtual "single realization" plume release data sets from the Virtual THreat Response Emulation and Analysis Testbed (VTHREAT) and data from the fusion Field Trials 2007 (FFT07). The end-to-end prototype of this system that has been developed to illustrate its use within the United States (US) Joint Effects Model (JEM) will be demonstrated.

关键词： Atmosphere Chemical Biological Transport Dispersion Source Parameter Estimate Variational Adjoint

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multisensor. multisource information fusion: architectures, algorithms, and applications 2010

Multisensor, Multisource Information Fusion: Architectures, ...

引用

multisensor. multisource information fusion: architectures, algorithms, and applications 2010

ISBN: (纸本)9780819481740

The proceedings contain 23 papers. The topics discussed include: capturing dynamics on multiple time scales: a multilevel fusion approach for cluttered electromagnetic data;classification of terrain using multi-resolution satellite/aerial imagery and lidar data;data fusion and classification using a hybrid intrinsic cellular inference network;fusion of ESM reports through Dempster-Shafer and Dezert-Smarandache theories;level 0-2 fusion model for ATR using fuzzy logic;multi-layered context impact modulation for enhanced focus of attention of situational awareness in persistent surveillance systems;global evaluation of focused Bayesian fusion;multiple hypothesis tracking of two persons using a network of lidar sensors with stationary and directional beams;a copula-based semi-parametric approach for footstep detection using seismic sensor networks;and integrating perception and problem solving to predict complex object behaviors.

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Hidden markov model for multimodal biometrics score fusion

Hidden markov model for multimodal biometrics score fusion

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multisensor. multisource information fusion: architectures, algorithms, and applications 2011

作者： Zheng, Yufeng Alcorn State University Alcorn State MS 39096 United States

ISBN: (纸本)9780819486387

There are strong evidences of that multimodal biometric score fusion can significantly improve human identification performance. Score level fusion usually involves score normalization, score fusion, and fusion decision. There are several types of score fusion methods, direct combination of fusion scores, classifier-based fusion, and density-based fusion. The real applications require achieving greater reliability in determining or verifying person's identity. The goal of this research is to improve the accuracy and robustness of human identification by using multimodal biometrics score fusion. The accuracy means high verification rate if tested on a closed dataset, or a high genuine accept rate under low false accept rate if tested on an open dataset. While the robustness means the fusion performance is stable with variant biometric scores. We propose a hidden Markov model (HMM) for multiple score fusion, where the biometric scores include multimodal scores and multi-matcher scores. The state probability density functions in a HHM model are estimated by Gaussian mixture model. The proposed HMM model for multiple score fusion is accurate for identification, flexible and reliable with biometrics. The proposed HMM method are tested on three NIST-BSSR1 multimodal databases and on three face-score databases. The results show the HMM method is an excellent and reliable score fusion method. © 2011 SPIE.

关键词： Hidden Markov models

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multisensor.Data fusion with Disparate Data Sources

Multisensor Data Fusion with Disparate Data Sources

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Conference on multisensor. multisource information fusion - architectures, algorithms and applications 2010

作者： Minor, Christian P. Hammond, Mark H. Johnson, Kevin J. Rose-Pehrsson, Susan L. Nova Res Inc 1900 Elkin St 320 Alexandria VA 22308 USA US Navy Naval Res Lab Washington DC 20375 USA

ISBN: (纸本)9780819481740

In many instances, sensing tasks are best addressed with multiple sensing modalities. However, fusion of the outputs of disparate sensor systems presents a significant challenge to forming a cohesive sensing system. A discussion of strategies for fusion of disparate sensor data is presented and illustrated with examples of real time and retrospective data fusion for multisensor.systems. The first example discussed is a real-time system for situational awareness and the detection of damage control events in ship compartments. The second example is a retrospective data fusion framework for a multisensor.system for the detection of buried unexploded ordnance at former bomb and target ranges.

关键词： data fusion multisensor.system fire detection UXO remediation

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Level 0-2 fusion model for ATR using fuzzy logic

<i>Level 0</i>-<i>2</i> fusion model for ATR using fuzzy log...

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Conference on multisensor. multisource information fusion - architectures, algorithms and applications 2010

作者： Hester, Charles F. Dobson, Kelly K. U.S. Army Aviation and Missile Research Development and Engineering Ctr. United States

ISBN: (纸本)9780819481740

The JDL model for fusion provides a structure for fusion of multispectral data at all levels. Fused data provides improved performance in Automatic Target Recognition (ATR). Critical to the overall fusion performance, however, is the low level(0-2) fusion of sensory and context information. Loss of information must be avoided at this level, but complexity must be reduced. A model is presented that uses fuzzy sets to form entities and capture the information needed for target recognition. Examples using multi-spectral imagery will be presented.

关键词： fuzzy logic ATR level 0-2 fusion JDL model

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Application of the JDL Data fusion Process Model for Cyber Security

Application of the JDL Data Fusion Process Model for Cyber S...

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Conference on multisensor. multisource information fusion - architectures, algorithms and applications 2010

作者： Giacobe, Nicklaus A. Penn State Univ Coll Informat Sci & Technol University Pk PA 16802 USA

ISBN: (纸本)9780819481740

A number of cyber security technologies have proposed the use of data fusion to enhance the defensive capabilities of the network and aid in the development of situational awareness for the security analyst. While there have been advances in fusion technologies and the application of fusion in intrusion detection systems (IDSs), in particular, additional progress can be made by gaining a better understanding of a variety of data fusion processes and applying them to the cyber security application domain. This research explores the underlying processes identified in the Joint Directors of Laboratories (JDL) data fusion process model and further describes them in a cyber security context.

关键词： Cyber Security Network Security Data fusion JDL Data fusion Process Model Situational Awareness

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Classification of terrain using multi-resolution satellite/aerial imagery and LiDAR data

Classification of terrain using multi-resolution satellite/a...

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Conference on multisensor. multisource information fusion - architectures, algorithms and applications 2010

作者： Kocher, Brian R. Thomas, Alan M. Georgia Inst Technol Georgia Tech Res Inst Atlanta GA 30332 USA

ISBN: (纸本)9780819481740

High resolution LiDAR data is used to augment spectral data to improve resolution/accuracy. Digital elevation information, texture information, and spectral data are all combined into a single dataset and different clustering algorithms are used on the raster information and compared with clusters of spectral data alone. Long term goals of the work are to find efficient and effective methods of combining different data sets of varying resolution from different sources into a single dataset for analysis to improve data and classification resolution and accuracy.

关键词： image fusion image processing texture multispectral imagery lidar data material classification

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